Ep 813: The Strategic Case For Sourcing

0:00When more people apply for jobs, fewer applications actually get read properly. When fewer applications get read, people apply for even more jobs. Inbound recruiting is stuck in a loop with no obvious way out. So where does hiring go from here? Keep listening to find out. Support for this podcast comes from Juicebox. If you're a recruiter, sourcing can quickly become your full-time job. You've got open recs, you've got a deadline, and you're spending the first two hours of your day trying to find people who might be a fit, scrolling the web, tweaking Boolean strings, sending faulty messages to get three replies.

0:42That is what Juicebox was built to fix. Juicebox is an AI recruiting platform that actually understands what you're looking for. You describe who you're looking for in plain English, and it services candidates across 800 million profiles from GitHub, Stack Overflow, Google Scholar, and more. No bullion, no manual filtering. And it doesn't stop at search. Juicebox personalises outreach for each candidate automatically, pulling in from their past experience or even flagging mutual connections at your company. You can send hundreds of personalised outreach messages weekly at scale. Recruiting teams at 5 ,000 plus companies like Notion, Ramp, and Cursor use Juicebox to source faster, reach further and delegate the most manual parts of their sourcing work so they can focus on what makes the recruiting process feel more human.

1:37You can try Juicebox free today by going to juicebox.ai and also use the code matalder15, that's matalder15, to get 15 % off your first annual plan.

1:56more of scientific discovery, more of technical advancement and material progress in your lifetime and mine, than in all the ages of history.

2:09Hi there, welcome to episode 813 of Recruiting Future with me, Matt Alder. AI has disrupted the dynamics of hiring. Candidates can now apply to hundreds of roles in a single click, while legal and regulatory constraints limit how far recruiters can use AI to review what comes in. The result is a flood of applications that just keeps on growing. With the inbound recruiting channel under this much pressure, sourcing offers a different equation. It's a channel where employers set the quality bar themselves, and AI has fundamentally changed to what it can deliver. The implications reach beyond pipeline quality.

2:52New approaches to sourcing could transform the candidate experience and open career paths for job seekers that traditional approaches to hiring would just never surface. So what does it take to make sourcing a genuine strategic priority? My guest this week is David Paffenholtz, co-founder and CEO of Juicebox. In our conversation, David explains what's driving the inbound challenges we're seeing, how AI is transforming what sourcing can do, why every role could get the executive search treatment in the future, and what this could all mean for candidates and their careers. Hi, David, and welcome to the podcast.

3:31Hey, Matt. Thanks for having me on. An absolute pleasure to have you on the show. Start off by just introducing yourself and telling everyone what you do. For sure. I'm David, co-founder of Juicebox, Juicebox an AI recruiting platform. We help our customers, source, reach out to and manage the best candidates. Tell us a little bit about the backstory, a bit about you and why you built Juicebox. My co-founder, Sean, and I started the business in 2022, right before ChatGPT was released. And we had this new paradigm of technology to build with. And so we had this thesis that we believed that search, specifically finding the right person for role, could be fundamentally changed using LLMs.

4:19And so that was the initial thesis that we had, and we started building. And at the time, the initial versions of large language models, the underlying tech we had in the first version of ChatGPT, weren't that good yet. And so the first versions of the product were directionally promising, but didn't quite get you the results that you wanted. And so we had this belief, though, or this moment of, okay, this is what the future will look like. Let's keep on building in that direction. And so that's what we've kept on doing. The product started getting strong traction in 2024. And now over the past years, we've skilled to work with over 5 ,000 customers, ranging from independent recruiters or small recruiting agencies all the way to Fortune 10 companies running their recruiting process on Juicebox.

5:08Time acquisition is in a really sort of strange paradox at the moment. There's a record volume of applications that many companies are getting for lots of different reasons. while we're still hearing the same thing about skill shortages, really hard to fill roles. What's driving all of this? What are you seeing as the forces in play here? Yeah, so there's this kind of really interesting paradox going on in recruitment where AI is being used more effectively by the applicant side than the recruiting side. And so what that specifically means is as an applicant today, the default assumption is that you are using an AI bulk apply tool And a lot of those tools today even have built-in AI personalization.

5:55And so that means that candidates can bulk-tailor resumes to the specific roles, bulk-tailor cover letters and more. And so they're in one click can do 500 applications. And so the overall candidate application volume has increased massively. And there's a few different data points that some of the ATSs, including Greenhouse, have published to back that up. And so we're seeing this huge surge in application volume. Now on the recruiter side, there's a lot more limitations on how AI can be used to review those applications. And so typically with the medium customer that we speak with, that's still a manual process.

6:34And so while candidates can use AI to massively amplify the amount of roles they apply to, the impact that AI has on the recruiting side in terms of reviewing those applications is still relatively low, primarily driven by the legal and regulatory implications that exist from using AI to evaluate applicants. And so it creates this self-reinforcing loop where the more people bulk apply, the less likely it is that their resume will be reviewed, which then in turn creates an incentive to apply even more. And so inbound as a channel is kind of having a tough time at the moment where it's hard to see where the end to that loop will be or what will cause that to change.

7:13and I speak about it like almost every day with different customers and different ways to solve it and I think that's something that the industry is still going to have to continue to figure out. It's interesting and I suppose one of the real issues is that TA teams are being squeezed in terms of the resources that they've got, the people that they've got. There's this huge volume of applications but still creating challenges as we've said. I mean, given everything that's going on, given the fact that TA leaders' budgets are under kind of intense pressure and attention at the moment. How would you kind of expand on that?

7:47And what's the business case for putting sourcing back to the top of the list here? So if we think of the kind of inbound channel having this current mixed state, and it definitely being a less reliable one for us to get the calendar pipeline that we need, it kind of creates that question of, where are we going to invest our resources or where do we think we can take control in our process? And one of the few channels, or perhaps the only channel, that is truly under the control of the TA team is on outbound. And so sourcing, you can control the candidate quality that you bring in, and to some extent you can control the volume of candidates that you bring in based on how much you prioritize that channel.

8:32And so when we look at the mix-up that a team might have in terms of their candidate pipelines, we often ask, hey, is sourcing or outbound where you want it to be and what would be your dream state on that? In almost every case, the dream state on sourcing is significantly higher than where it is today. The main issue is capacity of being able to go and source, especially if it's a full-stack recruiting team or only a small dedicated sourcing function. That's often where we see the desire to increase that more, but no available time or prioritization or framework to be able to actually get the sourced candidates into the pipeline.

9:12And so then if we graph that, or if we think of the actual pipeline as a visual object, it's going to be widening right now because of the inbound volume, but the quality is going to be low, so the actual throughput of that timeline is going to be really low. Versus with sourcing, we can slightly widen the funnel, but with really high quality throughput. And so the end result from that funnel should be a lot better. Sourcing as a way of working has been around for a long time now. We've had technology that's helped with sourcing for a long time now. There are lots of TA leaders who started their career as sourcers.

9:46So there'll be people listening, leaders listening, who feel that their sourcing is where it needs to be. It's in a good place. What's changed in the last year or so that should make them want to sort of look at their strategy again? I'd kind of challenge the assumption that the sourcing is in a kind of good place for most organizations. I think we consistently see it that people have a desire to invest more into sourcing. And I think part of the reason for that or the underlying trend is, you know, the skill sets that people are looking for in the era of AI has changed quite dramatically, which also might mean that the right candidate for a given role doesn't necessarily have the exact job title to match it.

10:31And that can also make it very hard for candidates to self-discover, hey, this is the right role for me, and kind of puts the burden on the employer to go and find the right candidate for the role instead. And I think that's only going to accelerate, especially in the next couple of years, as there's kind of this shift towards, to what extent is the average job scope more AI enabled, or to what extent has that changed? And I think especially companies that are leaning into AI transformation or trying to invest in that, We'll also need to think about different ways to acquire talent to kind of continue that AI first path.

11:02Yeah, I completely agree with you. I think the makeup of the workforce is changing. Job titles are changing. The way that people are found is changing. So it's just such a dynamic market at the moment. One of the interesting things for me, which has come up a few times in conversations I've had with TA leaders on the podcast. In fact, it first came up with an employer who does massive volumes of recruitment. And it's this kind of sense that AI automation, the tools and technologies that we've now got, could take us to a place where all recruiting becomes like executive search. Is that something that you agree with?

11:41And how would it work in practice if you do? That's one of our kind of core theses, is that the future of recruiting will look more like executive search. And now what that means, one layer below, is that the amount of attention and effort that we put both into the planning process for search, so mapping out where do we expect talent to be, what are we actually looking for in the right person, and how large do we think that pool is. to then, two, being able to cover and actually exhaustively look at that pool. And then, three, engaging with that candidate through a really relationship-first approach where the recruiter's able and has the time to build that relationship with the candidate.

12:20And so I'd say those are the three largest distinct elements of actually treating recruiting like an executive search. And I think all three of those parts require some change to how recruiting processes look today. but most importantly they require the time and being able to invest that time into doing those things. When we think about Juicebox or the products that we develop we have two lenses. One, are we able to help self-time on the day-to-day work be that on sourcing, be that on updating the ATS based on sourced candidates, etc. But then two, are we creating the tooling or giving the platform that helps raise the bar and do some of that work that looks more like executive search So I think one of the areas that comes to mind immediately is on the talent mapping side and being able to provide pretty deep insights and data.

13:10I think historically that's almost kind of been viewed as a separate process. Some companies have dedicated research teams that are responsible for that. But that also often means that it doesn't get done for every role or it only gets done for senior level roles or like super high priority roles. When in fact the data should be available for every role. In fact, it can be tied into the actual search that someone's setting up in a sourcing platform. because that has the underlying data to be able to understand, okay, this is what the talent pool looks like. Here's where we might run into limitations.

13:39Here is where there's really strong pockets of candidates. And so we try to always think from that lens in terms of how can we enable a team to both save time, but then also raise the bar. And in my view, the raising the bar piece is what then gets closest to the executive search side. What are the implications for recruiters? So how do you see the role of the recruiter evolving and also where does human judgment, recruiter judgment sit in all of this as things evolve? Yeah, I think the role of the recruiter evolves more and more into acting as an advisor or consultant to two different stakeholders.

14:18One, the internal stakeholders, so be that the hiring manager, leadership, whoever they're working with internally to be able to map out the role and define what the persona should look like. and two, the candidate. And so the relationship that they're building with the candidate and the advice they're able to share with the candidate as well. And so I think to be able to really invest in both of those relationships, they have to be equipped with data. And so especially on the internal side, what have we seen from previous searches? What does the market look like? And how can we make better decisions as we're setting up the search or calibrating on the search?

14:54And I think those are areas is that we are now in a unique time where with LLMs and new AI tooling, we can actually provide really good advice on those topics too. What does the future look like? I mean, if we sort of extrapolate this all out, how do you think hiring itself is going to evolve? What are things going to be like in two or three years at a time? Or what do you hope they'll be like? So my hope is that there'll be two big changes. One, the way that people and roles are matched looks very different from today, primarily because we're able to predict someone's success in a role more based on experiences and skills rather than job title being the same as what they previously had.

15:43And so a lot of the mobility that used to occur mainly through internal mobility or internal career switches can actually occur when people are switching jobs or going into a new role entirely because AI can help predict, hey, this person might have a really good chance at succeeding at this new role, despite on paper it being something that they haven't done before. And so as prediction one, we'll have more matches that are actually based on skills and kind of this promise of skills-based hiring that we've had for a while can actually come true in a way that maybe goes a little bit beyond those skills too.

16:16the second prediction or hope that I have is that the way that we treat candidates is going to be a bit more akin to that executive search process we talked about and so the relationship with candidates will be a lot stronger and I think that's going to be driven by increased competition in the hiring market and so if everyone is matching in a better way or finding people truly based on skills and fit I think there will be more competition for those candidates than there are today as well and so that's my second prediction for the industry. And then the third part, and this is, I don't know if it's like a fear or a question, but I'm coming back to what we discussed on the application side.

16:56I'm truly unsure how that will evolve. Will there be a point where there's some kind of incentive that decreases the number of applications again, or some of that AI application tooling gets changed? But that part I'm really unsure about and curious to observe. Yeah, I think that's really interesting. I think you've picked on three things that I completely match where I hope things are going as well. Just as a quick follow-up, particularly on the first one around skills. Are you seeing this happening already? Because obviously we've talked about this for a long time. AI certainly has the potential to deliver the kind of things that you're talking about.

17:30Is there any evidence that we're already moving in that direction? I certainly think so. So one of the easiest ways for me to have data to back that up is looking at the searches that our customers are doing in our platform today. And so if you compare it to a traditional sourcing process, usually you start defining hard filters, so like job title, location, competitive companies, etc. And basically those filters, or the more rigidity of those filters, cause you to kind of match your target persona, but also make it very hard for you to go beyond that. Because you're truly strict filtering on those specific set of filters.

18:09In the searches that are possible today, be that in the Juicebox platform or elsewhere, it's prompt-based. And so by definition, you're not just searching based on job title or experience. You're actually looking at the full profile saying, hey, based on my experience, if I look at this profile, do I have conviction that they could be a good fit in this role? And what skills or what evidence do I see to back that up? And so because of that reasoning that's actually being done in platform, the same judgment that would previously not be possible because a human could not look across 100 ,000 profiles and make that prediction.

18:42We actually see that in hiring processes today. And we see thousands of hires being made through that method. And so I think that's been the adoption of kind of AI-based search or AI-based sourcing, to me, is the biggest predictor that skill-based hiring is already happening today, even if people don't see it directly under the label of, hey, this is actually a skill-based hire. Just as a final question for you, as you've sort of been building and developing over the last few years, what's the thing that surprised you the most about the industry or about the technology or anything, really? I think the thing that I've been most positively surprised by is how consistently enthusiastic and open to new technology TA, both leaders, but also individual recruiters and sourcers are.

19:29And so I think there's generally been a lot of enthusiasm and appetite to try out new tooling, especially in an industry that for a long time has been kind of dominated by a small number of giant platforms. I've been very positively surprised by the appetite and enthusiasm for that. It's also one of the reasons that we made Juicebox a self-serve product compared to, again, an industry that's usually extremely sales-led. Our sales-led motion still makes up the majority of our revenue, but the majority of people who first explore Juicebox do so through our self-serve and free products. I think it's been really fun to see the energy and enthusiasm there is for this new wave of technology.

20:10David, thank you very much for talking to me. Thank you for having me. My thanks to David. You can follow this podcast on Apple Podcasts, on Spotify, or wherever you listen to your podcasts. You can search all the past episodes at recruitingfuture.com. On that site, you can also subscribe to our weekly newsletter, Recruiting Future Feast, and get the inside track on everything that's coming up on the show. Thanks very much for listening. I'll be back next time, and I hope you'll join me.

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